• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.383-386
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• 2014

Due to the development of communication technology, a conventional major business through PC, laptop or Tablet PC can be performed via a smartphone and it is increasing the user's convenience. At this point, the user prefers to connect to the Internet using the wireless network because it occurs an additional charge according to the amount of data to be transmitted when using a data communication through 3G or 4G. However, when using a wireless network, there is a possibility of several attacks such as easily steal or modulate the information from the outside or to gain access to personal information stored in the user's smartphone with man-in-the-middle attacks by using the fake AP. IIn this paper, we describe how you can detect the AP when you use LAN of the smartphone, were analyzed for this vulnerability, has not been approved. Furthermore, Also, we discuss ways which can enhance the security when user the access to the internet services (i.e., internet, public/private cloud service, etc.) via wireless network in smartphone.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.645-653
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• 2016

Ransomware was first created in 1999, but its existence become widely known in Korean by 2015. As information and communication technology have developed, the storage capacity of computer has enlarged, it accordingly is getting more important to effectively manage these information, rather than the information itself. In such situation, the ransomware break into other people's computer and encrypt an files without a user's permission. So, it adversely affect the user. In this paper, we monitor an access of a specific process to the file. And on the basis of this monitoring information, we detect whether the abnormal approach happened. Through the detection result, we block the permission about access to the file for a specific process. Using this method, we propose a blocking technique for the ransomeware's abnormal approach and encryption to the files.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.35-42
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• 2019

Recently, as the Internet and various wearable devices have appeared, Internet technology has contributed to obtaining more convenient information and doing business. However, as the internet is used in various parts, the attack surface points that are exposed to attacks are increasing, Attempts to invade networks aimed at taking unfair advantage, such as cyber terrorism, are also increasing. In this paper, we propose a feature selection method to improve the classification performance of the class to classify the abnormal behavior in the network traffic. The UNSW-NB15 dataset has a rare class imbalance problem with relatively few instances compared to other classes, and an undersampling method is used to eliminate it. We use the SVM, k-NN, and decision tree algorithms and extract a subset of combinations with superior detection accuracy and RMSE through training and verification. The subset has recall values of more than 98% through the wrapper based experiments and the DT_PSO showed the best performance.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.11-17
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• 2021

If a vulnerability in the software connected to the network to obtain the user's privilege, a remote attacker could gain the privilege to use the computer. In addition, in a user environment in which an operating system for a specific series is used a lot, if a problem occurs in the operating system, considerable damage can occur. In particular, If an error is a security vulnerability, it can be a very big problem. Various studies have been conducted to find and respond to vulnerabilities in such a situation. Among various security technologies, the fuzzing technology is one of the most effective technologies to find errors in software. In this paper, I designed and implemented a fuzzing agent that can detect buffer overflow vulnerabilities that can occur in various applications. Through this fuzzing agent, application developers will be able to realize a more secure computing environment in which they can discover and fix vulnerabilities in their own applications.

• KNOM Review
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• v.22 no.1
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• pp.11-19
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• 2019

As technology develops, the latest security threats on the network applied to users are increasing. By attacking industrial or corporate systems with malicious purposes, hackers cause many social problems such as confidential information leakage, cyber terrorism, infringement of information assets, and financial damage. Due to the complex and diversified threats, the current security personnel alone are not enough to detect and analyze all threats. In particular, the Supervisory Control And Data Acquisition (SCADA) used in industrial infrastructures that collect, analyze, and return static data 24 hours a day, 265 days a year, is very vulnerable to real-time security threats. This paper introduces security information and event management (SIEM), a powerful integrated security management system that can monitor the state of the system in real time and detect security threats. Next, we compare SIEM solutions from various companies with the open source SIEM (OSSIM) from AlienVault, which is distributed as an open source, and present cases using the OSSIM and how to utilize it.

• Smart Media Journal
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• v.7 no.1
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• pp.37-44
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• 2018

Utilizing sequence control and numerical computing, embedded devices are used in a variety of automated systems, including those at industrial sites, in accordance with their control program. Since embedded devices are used as a control system in corporate industrial complexes, nuclear power plants and public transport infrastructure nowadays, deliberate attacks on them can cause significant economic and social damages. Most attacks aimed at embedded devices are data-coded, code-modulated, and control-programmed. The control programs for industry-automated embedded devices are designed to represent circuit structures, unlike common programming languages, and most industrial automation control programs are designed with a graphical language, LAD, which is difficult to process static analysis. Because of these characteristics, the vulnerability analysis and security related studies for industry automation control programs have only progressed up to the formal verification, real-time monitoring levels. Furthermore, the static analysis of industrial automation control programs, which can detect vulnerabilities in advance and prepare for attacks, stays poorly researched. Therefore, this study suggests a method to present a discussion on an industry automation control program designed to represent the circuit structure to increase the efficiency of static analysis of embedded industrial automation programs. It also proposes a medium term translation technology exploiting LLVM IR to comprehensively analyze the industrial automation control programs of various manufacturers. By using LLVM IR, it is possible to perform integrated analysis on dynamic analysis. In this study, a prototype program that converts to a logical expression type of medium language was developed with regards to the S company's control program in order to verify our method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1119-1127
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• 2018

Most of the cyber attacks are caused by malicious codes. The damage caused by cyber attacks are gradually expanded to IoT and CPS, which is not limited to cyberspace but a serious threat to real life. Accordingly, various malicious code analysis techniques have been appeared. Dynamic analysis have been widely used to easily identify the resulting malicious behavior, but are struggling with an increase in Anti-VM malware that is not working in VM environment detection. On the other hand, static analysis has difficulties in analysis due to various packing techniques. In this paper, we proposed malware classification techniques regardless of known packers or unknown packers through the proposed model. To do this, we designed a model of supervised learning and unsupervised learning for the features that can be used in the PE structure, and conducted the results verification through 98,000 samples. It is expected that accurate analysis will be possible through customized analysis technology for each class.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.163-169
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• 2024

Anti-drone (anti-drone) is at the center of the debate over the failure to shoot down a North Korean drone that invaded the metropolitan area at the end of 2022. Anti-drone is a means of detecting and restraining drone flights in unauthorized airspace. Anti-drone technology is a key defense system for drone technology that is essential in the current illegal situation of various drones. We must be alert in the war in Ukraine, where the role of drones has increased. Drone attacks, which are not easy to defend, may determine the victory or defeat of the war. Competition for anti-drone technology development in countries around the world will rise. When new anti-drone technology emerges, drones that go beyond it will be developed. This study presented the current status of anti-drone by analyzing the defense system of domestic drones.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.283-285
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• 2020

본 논문에서는 시스템이 비정상적인 상태에 진입하였는지를 판단하여 공격에 대한 탐지를 효율적으로 수행할 수 있는 하드웨어 기반 보안 모니터링 기술에 대해 소개한다. 먼저 이벤트 기반으로 커널을 보호하는 모니터링 기법들에 대해 알아볼 것이다. 최종적으로 다양한 이벤트를 유연하게 모니터링할 수 있는 기법을 살펴보고, 이를 바탕으로 보안 하드웨어 모니터링 기법의 향후 연구방향을 모색하고자 한다.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.108-116
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• 2019

In this paper, we propose a method to apply artificial intelligence technology efficiently to integrated security control technology. In other words, by applying machine learning learning to artificial intelligence based on big data collected in integrated security control system, cyber attacks are detected and appropriately responded. As technology develops, many large capacity Is limited to analyzing individual logs. The analysis method should also be applied to the integrated security control more quickly because it needs to correlate the logs of various heterogeneous security devices rather than one log. We have newly proposed an integrated security service model based on artificial intelligence, which analyzes and responds to these behaviors gradually evolves and matures through effective learning methods. We sought a solution to the key problems expected in the proposed model. And we developed a learning method based on normal behavior based learning model to strengthen the response ability against unidentified abnormal behavior threat. In addition, future research directions for security management that can efficiently support analysis and correspondence of security personnel through proposed security service model are suggested.